Testing autonomous driving vehicles refers to a quality assurance process in which diverse validation activities are performed based on well-defined quality assurance standards and assessment criteria. In a quality validation process, unmanned autonomous driving vehicles are validated at different levels (component, integration, and system) based on the pre-defined quality requirements to assure system quality in algorithms, functions, components, behaviors, connectivity, sensing, performance, intelligence, and decision makings in diverse contexts and conditions. To reduce the cost and increase the testing efficiency in the autonomous driving industry, simulation testing receives increasing attention and effort in recent years. A high-fidelity simulation software usually contains the mathematical representations of the environment, the dynamics of autonomous vehicles and surrounding vehicles, the sensors models, etc., at different levels, and is needed to facilitate the testing and development of autonomous driving systems. In order to perform efficient simulation testing, techniques for optimizing and accelerating testing processes are in great demand.
This challenge is set up as a platform to address this demand and advocate the importance and need for quality validation and automation for autonomous driverless cars. This platform provides a global competition opportunity for international student teams and professional teams to develop diverse simulation testing techniques and approaches in test scenario generation and automation.

For more details, please visit our website: http://av-test-challenge.org/index.html#